Does public transit improvement affect commuting behavior in Beijing, China? : A spatial multilevel approach

Developing countries like China have experienced substantial city transformations over the past decade. City transformations are characterized by transportation innovations that allow individuals to access to speedy commuting modes for work activities and offer potential influences on commuting behavior. This paper examines the potential effects of subway system expansion in Beijing on commuting behavior. Our methodological design controls for spatial effects by employing Bayesian multilevel binary logistic models with spatial random effects. Using cross-sectional individual surveys in Beijing, the results suggest that there is a significant rise in subway commuting trips while non-motorized and bus commuting trips are reduced with the new subway expansion. Model comparison results show evidence about the presence of spatial effects in influencing the role of built environment characteristics to play in the commuting behavior analysis

Spatial variations in amenity values: new evidence from Beijing, China

Using parks as an example, this paper explores the robustness and sources of spatial variation in the estimated amenity values using an extended geographically weighted regression (GWR) technique. This analysis, illustrated with estimates using geo-coded data from Beijing’s residential land market, has three important implications. First, it provides a powerful estimation strategy to evaluate how sensitive GWR parameters are to unobserved amenities and complementarities between amenities. Second, it compares the spatial variation patterns for the marginal prices of proximity to parks, estimated using a range of GWR model specifications. The answers generated using the GWR approach still reveal a significant underlying problem of omitted variables. Finally, it highlights the importance of conceptualizing amenity values not just in terms of their structural characteristics but how those characteristics interact with or are conditioned by local social, economic, and other contextual characteristics

Urban rail investment: lessons from Beijing

Posted by Wenjie Wu, LSE While British politicians argue about infrastructure, Chinese policymakers have been laying it out. Decades of heavy investment in urban transport systems have reshaped the face of most Chinese cities. Between 2000 and 2008 alone, for example, the Beijing city government invested about 52 billion CNY (c. £5.2bn) on new rail transit construction, with a subsequent investment of 105 billion CNY (c. £10bn) in the four years to 2012

Empirical essays on real estate, local public goods and happiness: evidence from Beijing

This thesis explores the real estate and happiness consequences of public investment in local public goods improvements by using unique micro-geographical data from Beijing; it focuses on the spatial variations in park amenity values, and on the impact of transport improvements on land prices and homeowners’ happiness. Despite intense public interest, little is known about these effects. This thesis aims to fill these gaps. First, I explore the impact and sources of variations of park proximities as capitalized into the residential land prices. This analysis, using geographically-coded data from Beijing, provides new insights on the ways in which land markets capitalize the values of proximity to parks and suggests that this is highly dependent on the parcel’s location and local contextual characteristics. Next, I examine the real estate consequence of public investment in transport improvements using a rich data set of vacant land parcels in Beijing. I use a multiple intervention difference-in-difference method to document opening and planning effects of new rail stations on prices for different land uses in affected areas versus unaffected areas. Residential and commercial land parcels receiving increased station proximity experience appreciable price premiums, but the relative importance of such benefits varies greatly over space and local demographics. Finally, I investigate the impact of transport improvements on happiness that altered the residence-station distance for some homeowners, but left others unaffected. My estimation strategy takes advantage of micro happiness surveys conducted before-and-after the building of new rail stations in 2008 Beijing. I deal with the potential concern about the endogeneity in sorting effects by focusing on “stayers”and using non-market housings with pre-determined locations. I find the significantly heterogeneity in the effects from better rail access on homeowners’ happiness with respect to different dimensions of residential environment. The welfare analysis results suggest strong social-spatial differentiations. In combination, the three papers of this thesis make important contributions to a growing literature on public infrastructure, land market and happiness

Theoretical and experimental study on cable vibration reduction with a TMD-MR damper

Stay cables are vulnerable to dynamic excitations because of their low intrinsic damping. Excessive cable vibrations cause frequent maintenance and are detrimental to the safety of the entire bridge. Targeting the severe cable vibration problem, in addition to using the existing Magnetorheological (MR) damper, the current study proposes a new type of damper, called the Tuned Mass Damper-Magnetorheological (TMD-MR) damper. Theoretical and experimental investigations for the damper performance on the cable vibration reduction are conducted, which provides the necessary research support for practical implementation. Experiments on the individual MR damper are carried out first to gain some experience on the damper itself. The MR damper is then added to the cable to demonstrate its effectiveness for vibration reduction, both passively and semiactively. Based on the obtained information, a TMD-MR damper is manufactured according to the vibration level of the experimental cable. The designed TMD-MR damper is then added to the experimental cable, and possible factors that may affect the damper performance are investigated experimentally. To get a profound and extended understanding of the TMD-MR damper performance, a simple horizontal taut cable-damper model, and then a more refined analytical model for the inclined sagged cable-TMD-MR system, are established. Through a parametric study on the achieved modal damping of the system, a thorough investigation on the effect of the cable or the damper parameters on the TMD-MR damper performance is carried out. The design process of the damper for the rain-wind induced cable vibration reduction is also explained based on the parametric study. Though this study focuses on the research of the proposed TMD-MR damper, the viscous damper is also considered for comparison purposes. The present research demonstrates not only that semiactive control is more efficient than the passive control, but also that MR dampers are failure-free devices for vibration control since their passive mode provides damping too. The proposed TMD-MR damper combines the flexibility of the TMD damper and the adjustability of the MR damper, and therefore is a promising way to reduce the cable vibration, though further research is necessary to warrant field applications

Logical gaps in the approximate solutions of the social learning game and an exact solution

After the social learning models were proposed, finding the solutions of the games becomes a well-defined mathematical question. However, almost all papers on the games and their applications are based on solutions built upon either an add-hoc argument or a twisted Bayesian analysis of the games. Here, we present logical gaps in those solutions and an exact solution of our own. We also introduced a minor extension to the original game such that not only logical difference but also difference in action outcomes among those solutions become visible.Comment: A major revisio

Representation Learning for Scale-free Networks

Network embedding aims to learn the low-dimensional representations of vertexes in a network, while structure and inherent properties of the network is preserved. Existing network embedding works primarily focus on preserving the microscopic structure, such as the first- and second-order proximity of vertexes, while the macroscopic scale-free property is largely ignored. Scale-free property depicts the fact that vertex degrees follow a heavy-tailed distribution (i.e., only a few vertexes have high degrees) and is a critical property of real-world networks, such as social networks. In this paper, we study the problem of learning representations for scale-free networks. We first theoretically analyze the difficulty of embedding and reconstructing a scale-free network in the Euclidean space, by converting our problem to the sphere packing problem. Then, we propose the "degree penalty" principle for designing scale-free property preserving network embedding algorithm: punishing the proximity between high-degree vertexes. We introduce two implementations of our principle by utilizing the spectral techniques and a skip-gram model respectively. Extensive experiments on six datasets show that our algorithms are able to not only reconstruct heavy-tailed distributed degree distribution, but also outperform state-of-the-art embedding models in various network mining tasks, such as vertex classification and link prediction.Comment: 8 figures; accepted by AAAI 201